Location: San Francisco or Croatia

Type: Full-time

Reports to: CEO

About Daytona

Daytona is the infrastructure layer for AI agents. We provide secure, isolated, instantly available sandboxes where agents run code, use computers, and train. Our platform powers agent workloads, reinforcement learning, and developer environments for some of the largest AI companies in the world. We closed our Series A earlier this year and have already grown 10x since. We are a small, senior team moving extremely fast.

The role

You will own the product for Daytona's serverless GPU sandboxes, embedded directly in the GPU pod with its engineering lead. GPU compute behind a single API call is a new category. Your job is to decide what we build, for whom, in what order, and at what price.

What You'll Do

• Own the GPU sandbox roadmap: instance shapes, GPU types, regions, quotas, snapshot/pause semantics, and the developer experience around all of it
• Live with customers: AI agent companies, RL training teams, and inference workloads. Turn their pain into a ranked backlog
• Own pricing and packaging inputs: per-second GPU billing, margin modeling with engineering, and competitive positioning against Modal, RunPod, and other Serverless GPU Providers.
• Define and track the metrics that matter: activation, time to first GPU sandbox, utilization, net revenue retention on GPU SKUs
• Write crisp specs, cut scope ruthlessly, and ship with the pod every week
• Feed capacity planning: work with engineering and finance on GPU procurement signals from demand data

What We're Looking For

• 5+ years in product management, with real time spent on infrastructure, cloud compute, or developer platforms
• Technical fluency: you can hold your own in a conversation about GPU scheduling, virtualization isolation models, and API design. You don't need to write the code, but you can't be bluffed
• Evidence you have shipped developer-facing products that developers actually adopted